More evidence of testing errors. I am going to show you a graph of the number of admissions per case diagnosed with COVID. First, let’s think what it should show.

At the beginning the admissions per case will be high because the only testing was done in hospitals. As we increased testing in the community and found more cases it should fall and keep falling.

In August and September, when we were mass testing people in their 20s who don’t go to hospital much, there should be another fall.

Here is the graph

Looks like we predicted. But what’s going on in June? It’s hard to tell because of the scale so let’s forget about the beginning and just look from 1st June.

This is odd. There is a in the first half of June and another at the beginning of September despite all the testing of university students at that time. Were these outbreaks of a more severe COVID? There is no evidence of more severe strains.

Could this be a testing error? If most of what we were seeing were false positives then the number of tests done would influence the results. Increasing the number of tests done in hospital would make the line go up and increasing them in the community would make the line go down

I am going to show you another graph now. This is a graph of the number of tests in hospital (which create false positive admissions) divided by the number of tests in the community (which create false positive cases). I left a 10 day lag between the two as for the first graph.

This also has a rise at the beginning of June and another rise at the beginning of September.

Let’s see the two side by side. This is very suspicious to me. Am I wrong? Have I missed a biological explanation?

@threadreaderapp unroll